- Design and lead the development of scalable, production-grade AI systems with a strong backend focus

- Build and manage modular AI pipelines including data preprocessing, training, deployment, and monitoring

- Develop APIs, microservices, and backend services to integrate AI models into products and real-time systems

- Collaborate with DevOps, data, and infrastructure teams to deploy models across cloud, hybrid, or edge environments

- Ensure code quality, maintainability, and reliability through CI/CD, containerization, and version control best practices

- Optimize systems for performance, scalability, and hardware-aware deployment (GPUs, edge devices, etc.)

- Implement best practices for model reproducibility, governance, and observability

- Mentor junior engineers and promote engineering excellence in scalable system design

Must-Have Skills :

- Strong backend development experience in Python (Go or Rust is a plus)

- Hands-on experience with backend frameworks such as FastAPI, Flask, gRPC, or similar

- Solid understanding of AI/ML system architecture and lifecycle management

- Experience with Docker, Kubernetes, and CI/CD pipelines in production environments

- Strong knowledge of distributed systems, asynchronous processing, and API design

- Familiarity with model tracking/versioning tools such as MLflow, DVC, or Weights & Biases

- Production experience with Linux-based systems and containerized deployments

Nice-to-Have :

- Exposure to computer vision use cases and frameworks (e.g., YOLO, UNet, transformers)

- Experience with streaming or real-time inference systems (Kafka, DeepStream, etc.)

- Hands-on experience with edge AI hardware and inference optimization (Jetson, ONNX, TensorRT)

- Familiarity with major cloud platforms (AWS, GCP, Azure)

- Experience with synthetic data generation or data augmentation pipelines

- Contributions to open-source projects or publications in AI systems or ML infrastructure

Qualifications :

- B.E./B.Tech/M.Tech in Computer Science, Software Engineering, or a related field

- 5+ years of experience in software engineering, preferably in AI/ML product environments

- Proven track record of designing and deploying production-grade AI systems